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Re: st: mlogtest after mlogit


From   Chiara Mussida <cmussida@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: mlogtest after mlogit
Date   Tue, 25 Oct 2011 13:18:20 +0200

On 25 October 2011 12:57, Nick Cox <njcoxstata@gmail.com> wrote:
> If you look at the code of -mlogtest- the warning message that worries
> you is when a helper program -_pecats- produces output that is
> inconsistent. After your -mlogit- call you can run -_pecats- followed
> by -return list-. In a well-behaved case, you will get output like
> this in which r(numcats) matches the number of elements in r(catvals).
> Your output will probably not match up. I don't know why that might
> be, but I doubt that the category frequencies are somehow the issue.
> (For "STATA" read "Stata".)
>
> . _pecats
>
> . return list
>
> scalars:
>            r(numcats) =  9
>             r(refval) =  3
>
> macros:
>            r(catnms8) : "1 2 4 5 6 7 8 9 3"
>            r(catvals) : "1 2 4 5 6 7 8 9 3"
>             r(catnms) : "1 2 4 5 6 7 8 9 3"
>              r(refnm) : "3"
>
Exactly Nick and thanks: when I type -_pecats- and -return list- I get:

 return list

scalars:
            r(numcats) =  9
             r(refval) =  .

macros:
            r(catnms8) : "1 2 3 4 5 6 7 8 9"
            r(catvals) : "1 2 3 4 5 6 7 8 9 __000000"
             r(catnms) : "1 2 3 4 5 6 7 8 9"

where as you correctly assumed, I do not have the match between
r(numcats) and  r(catvals), but something like __000000 which does not
allow a perfect matching. I still do not know why it happens.





>
> On Tue, Oct 25, 2011 at 11:10 AM, Chiara Mussida <cmussida@gmail.com> wrote:
>> On 25 October 2011 01:10, Richard Williams
>> <richardwilliams.ndu@gmail.com> wrote:
>>> At 05:59 AM 10/24/2011, Muhammad Anees wrote:
>>>>
>>>> have you tried -mlogtest, all- to verify if these categories have no
>>>> other issues. Otherwise the test on -combine- might have resulted
>>>> becaure some of the categories had small or no observations so
>>>> checking the condition of equal coefficients from -comibe- did not
>>>> work.
>>>
>>> I agree - I get nervous about using multiple-outcome commands like mlogit
>>> with lots and lots of independent variables. You may be spreading the data
>>> too thin. But, before taking this too much further, I'd like the original
>>> poster to confirm that the most current version of mlogtest is indeed being
>>> used. Otherwise we might be talking about a problem that was fixed 6 months
>>> ago. Also, it might be good to present a frequency of the dependent
>>> variable. Long and Freese's commands are sometimes pickier about coding than
>>> Stata is, e.g. they sometimes don't like non-integer coding. Also, you would
>>> see if some of the categories have very small frequency counts. Finally, I
>>> would run a simple model with only one or two independent variables followed
>>> by mlogtest. If the simple model works and the more complicated one doesn't,
>>> that might indicate problems with one or more of the added variables or with
>>> the data being spread too thin to do the test.
>>>
>>>
>> Dear All, I confirm that my current version of mlogtest is and was the
>> one indicated by Nick, precisely:
>>
>> . which mlogtest, all
>>
>> C:\Program Files\Stata12\ado\updates\m\mlogtest.ado
>> *! version 1.7.6 jsl 2009-10-18
>>
>> in terms of model estimates, I guess that the issue is related to the
>> relative frequency of my dependent variables categories':
>>
>>  ta transition
>>
>>  transition |      Freq.     Percent        Cum.
>> ------------+-----------------------------------
>>          1 |        271        0.70        0.70
>>          2 |        132        0.34        1.04
>>          3 |      1,119        2.90        3.94
>>          4 |        379        0.98        4.93
>>          5 |        722        1.87        6.80
>>          6 |     13,959       36.17       42.97
>>          7 |        388        1.01       43.98
>>          8 |        168        0.44       44.41
>>          9 |     21,450       55.59      100.00
>> ------------+-----------------------------------
>>      Total |     38,588      100.00
>>
>> e.g., categories 2 and 8 might be too small. Now, I cannot collapse my
>> dep variable in a reduced number of categories and I hope that
>> notwithstanding the STATA alert message after typing the test command
>> (below I copied all the results) do not bias my results. ps: for the
>> test N=25441 since the model estimates are referred to a subsample
>> (aged 15-64) of the overall population (38588).
>>
>> mlogtest, c
>>
>> Problem determining number of categories.
>>
>> **** Wald tests for combining alternatives (N=25441)
>>
>>  Ho: All coefficients except intercepts associated with a given pair
>>     of alternatives are 0 (i.e., alternatives can be combined).
>>
>> Alternatives tested|     chi2   df   P>chi2
>> -------------------+------------------------
>>       1-       2  |   18.576    5    0.002
>>       1-       3  |    5.990    5    0.307
>>       1-       4  |   13.565    5    0.019
>>       1-       5  |  148.448 5 0.000
>>       1-       6  |  178.434    5    0.000
>>       1-       7  |   33.226    5    0.000
>>       1-       8  |   68.938    5    0.000
>>       1-       9  |  311.133    5    0.000
>>       2-       3  |   19.911    5    0.001
>>       2-       4  |   23.931    5    0.000
>>       2-       5  |   68.619    5    0.000
>>       2-       6  |   68.197    5    0.000
>>       2-       7  |   24.027    5    0.000
>>       2-       8  |   55.161    5    0.000
>>       2-       9  |  127.081    5    0.000
>>       3-       4  |   36.426    5    0.000
>>       3-       5  |  438.391    5    0.000
>>       3-       6  |  703.923    5    0.000
>>       3-       7  |   59.553    5    0.000
>>       3-       8  |  103.537    5    0.000
>>       3-       9  | 1130.422    5    0.000
>>       4-       5  |  197.002    5    0.000
>>       4-       6  |  103.387    5    0.000
>>       4-       7  |   91.631    5    0.000
>>       4-       8  |  132.381    5    0.000
>>       4-       9  |  530.943    5    0.000
>>       5-       6  |  592.783    5    0.000
>>       5-       7  |  192.566    5    0.000
>>       5-       8  |  142.185    5    0.000
>>       5-       9  |  281.162    5    0.000
>>       6-       7  |  520.969    5    0.000
>>       6-       8  |  430.911    5    0.000
>>       6-       9  | 5946.722    5    0.000
>>       7-       8  |   24.867    5    0.000
>>       7-       9  |  231.357    5    0.000
>>       8-       9  |   82.933    5    0.000
>> --------------------------------------------
>>
>
> *
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>



-- 
Chiara Mussida
PhD candidate
Doctoral school of Economic Policy
Catholic University, Piacenza (Italy)

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